Computing resource monitoring systems have evolved and continue to evolve to keep up with the demands of the organizations that use them. Many organizations, for example, utilize computing resource monitoring systems for, among other reasons, evaluating one or more metrics associated with resources and applications that the organizations may utilize to support their businesses. Despite their many advantages, many modern computing resource monitoring systems are prone to data corruption or defects resulting in reduced availability of the data and potential data loss. For example, if a storage node within a computing resource monitoring system is damaged or rendered unavailable, the data stored within may accordingly become unavailable and, without redundancy, may be lost. Currently, many modern computing resource monitoring systems utilize a horizontal partition to store one or more metrics that, if lost, may result in any metrics that reside within the partition being unavailable for all reads and writes at any point in time. Additionally, these modern computing resource monitoring systems may be configured to monitor one or more services that may be automatically scaled according to customer and system demands. This, in turn, could exacerbate the impact of any unavailability of metrics associated with the resources and applications supported by the computing resource monitoring service. Adequately addressing these issues, such as through provisioning additional resources to adequately provide data redundancy in the event of one or more unavailable storage nodes, presents additional costs to the organizations that rely on the computing resource monitoring systems and the computing resource service provider that may provide the computing resource monitoring service to its customers.